{"title":"Revisiting Variation in the Somatic Mutation Landscape of Non-Small Cell Lung Cancer.","authors":"Vaibhavi Pathak, Koichi Tazaki, Minal Çalışkan","doi":"10.1016/j.xhgg.2025.100420","DOIUrl":null,"url":null,"abstract":"<p><p>Non-small cell lung cancer (NSCLC) is driven by a diverse array of somatic mutations. The vast majority of literature on NSCLC is based on targeted assays or small sample sizes, limiting their ability to provide a comprehensive view of NSCLC mutation profiles. Here, we analyzed genome-wide screen data (including WGS and WES) from 1,874 NSCLC subjects to identify molecular subtypes, putative driver genes, and explore the effect of intrinsic and extrinsic factors on somatic mutation profiles. We showed that genome-wide screen data supports existing knowledge, such as the TP53:KRAS mutation co-occurrence pattern as a key distinctive feature, but does not reveal additional broad molecular subtypes. In contrast, we demonstrated that low-frequency molecular subtypes or potential driver genes continue to be identified. Using driver gene identification algorithms, we found 50 potential driver genes including ANG, CDK10, CTDSP2, HOXA5, RBP4, and SPHK2, which show evidence of positive selection in NSCLC. Finally, we provided insights into the intrinsic and extrinsic covariates associated with the NSCLC somatic mutation landscape; while confirming associations with ethnicity (TP53, EGFR), NSCLC subtype (14 genes including KRAS, NFE2L2, STK11), and smoking history (KRAS, CSMD3, TP53), we dismissed gene-level associations with sex when other covariates are controlled for. The results presented here represent a concise up-to-date summary of variation in the somatic mutation landscape and carry importance for NSCLC geneticists, medical practitioners, and drug discovery scientists.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":" ","pages":"100420"},"PeriodicalIF":3.3000,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"HGG Advances","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.xhgg.2025.100420","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
引用次数: 0
Abstract
Non-small cell lung cancer (NSCLC) is driven by a diverse array of somatic mutations. The vast majority of literature on NSCLC is based on targeted assays or small sample sizes, limiting their ability to provide a comprehensive view of NSCLC mutation profiles. Here, we analyzed genome-wide screen data (including WGS and WES) from 1,874 NSCLC subjects to identify molecular subtypes, putative driver genes, and explore the effect of intrinsic and extrinsic factors on somatic mutation profiles. We showed that genome-wide screen data supports existing knowledge, such as the TP53:KRAS mutation co-occurrence pattern as a key distinctive feature, but does not reveal additional broad molecular subtypes. In contrast, we demonstrated that low-frequency molecular subtypes or potential driver genes continue to be identified. Using driver gene identification algorithms, we found 50 potential driver genes including ANG, CDK10, CTDSP2, HOXA5, RBP4, and SPHK2, which show evidence of positive selection in NSCLC. Finally, we provided insights into the intrinsic and extrinsic covariates associated with the NSCLC somatic mutation landscape; while confirming associations with ethnicity (TP53, EGFR), NSCLC subtype (14 genes including KRAS, NFE2L2, STK11), and smoking history (KRAS, CSMD3, TP53), we dismissed gene-level associations with sex when other covariates are controlled for. The results presented here represent a concise up-to-date summary of variation in the somatic mutation landscape and carry importance for NSCLC geneticists, medical practitioners, and drug discovery scientists.